Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method for streamlined data entry at a server, comprising: querying a cache for one or more most-recently-used (MRU) entities corresponding to a mobile device, wherein the cache stores a plurality of MRU entities based at least in part on a plurality of prior data logging events associated with the mobile device; automatically identifying one or more entities corresponding to the mobile device as most likely to be selected for data logging according to the queried one or more MRU entities; transmitting, for display at the mobile device, data that identifies the one or more entities and a first interface that accepts selection among the identified one or more entities: receiving a selection of a particular entity responsive to transmitting the data and the first interface; transmitting, for display at the mobile device, a second interface that includes a list of activities that fits on a single screen of the mobile device and accepts selection among the list of activities, wherein the list of activities is determined based at least in part on the selection of the particular entity; detecting a selection of an activity of the list of activities responsive to transmitting the second interface; transmitting, for display at the mobile device, a comment entry user interface comprising automatically generated ghost text, wherein the ghost text is automatically generated based at least in part on the selection of the particular entity and the selection of the activity; receiving, from the mobile device, an indication of a user input value from the comment entry user interface either accepting the ghost text or revising the ghost text; and storing, at a data store, an indication of at least the particular entity and the accepted or revised ghost text.
This invention relates to streamlining data entry for mobile devices by leveraging prior usage patterns to predict and pre-fill relevant information. The system addresses inefficiencies in data logging by reducing manual input steps, particularly in scenarios where users frequently log similar data. The method involves querying a cache to retrieve the most-recently-used (MRU) entities associated with a specific mobile device, where the cache is populated based on historical data logging events. The system then identifies entities most likely to be selected for logging and presents them to the user via a first interface. Upon selection of an entity, a second interface displays a concise list of activities that fits on a single screen, tailored to the chosen entity. After an activity is selected, a comment entry interface appears with automatically generated ghost text, which is pre-populated based on the entity and activity selections. Users can either accept or modify this text. The final logged data, including the entity and the accepted or revised comment, is stored in a data store. This approach minimizes user effort by predicting and pre-filling likely selections and comments, improving efficiency in data logging workflows.
2. The method of claim 1 , further comprising: receiving, from the mobile device, context-aware information comprising a location of the mobile device, a user token, a time of data logging, or a combination thereof; and updating the data store to include the context-aware information.
3. The method of claim 1 , wherein the identification of the one or more entities as most likely to be selected for data logging is based at least in part on access recency of records of the one or more entities, imminence of events linked to the one or more entities, geographic proximity of the one or more entities to the mobile device, or a combination thereof.
4. The method of claim 1 , wherein automatically identifying the one or more entities as most likely to be selected for data logging further comprises: identifying windows of time scheduled for events associated with the one or more entities; sensing imminence of the events associated with the one or more entities; and identifying the one or more entities as most likely to be selected for data logging based at least in part on the imminence of the events.
5. The method of claim 1 , wherein automatically identifying the one or more entities as most likely to be selected for data logging further comprises: determining geographic proximities of the one or more entities to the mobile device; and identifying the one or more entities as most likely to be selected for data logging based on the geographic proximities.
6. The method of claim 1 , wherein detecting the selection of the activity comprises: receiving, from the mobile device, an indication of the activity selection among the list of activities, wherein the automatically generated ghost text is based at least in part on the activity selection; and executing an activity corresponding to the activity selection against the selected entity, wherein the storing is based at least in part on the executed activity.
This invention relates to mobile device applications that facilitate user interactions with entities, such as contacts or records, by providing context-aware suggestions. The problem addressed is the inefficiency of manually entering data or selecting actions when interacting with entities in mobile applications, leading to a fragmented and time-consuming user experience. The invention describes a method for enhancing user interactions by automatically generating and displaying ghost text—pre-filled or suggested text—based on a user's selection of an activity from a list. The ghost text is dynamically generated based on the selected activity, providing contextually relevant input or instructions. When a user selects an activity (e.g., sending a message, scheduling an event, or updating a record), the system executes the corresponding action against the selected entity (e.g., a contact or database record). The results of this executed activity are then stored, ensuring that the system retains the context of the interaction for future reference or further automation. The method improves efficiency by reducing manual input and guiding users through predefined workflows, making interactions with entities more intuitive and streamlined. The ghost text and activity execution are tightly coupled, ensuring that the system adapts to user selections in real time. This approach is particularly useful in applications where quick, context-aware actions are critical, such as customer relationship management (CRM) tools, messaging apps, or productivity suites.
7. The method of claim 1 , wherein detecting the selection of the activity comprises: automatically selecting the activity among the list of activities, wherein the selected activity is identified as most likely to be selected by a user associated with the mobile device; and executing an activity corresponding to the activity selection against the selected entity, wherein the storing is based at least in part on the executed activity.
This invention relates to automated activity selection and execution in mobile device applications, addressing the problem of user inefficiency in manually selecting and performing repetitive tasks. The method involves analyzing user behavior to predict and automatically select the most likely activity a user will choose from a list of available activities. The system identifies the user's mobile device and associated user profile to determine the most probable activity selection based on historical data or contextual factors. Once the activity is automatically selected, the system executes the corresponding action against a selected entity, such as a file, application, or data object. The results of this executed activity are then stored, with the storage process influenced by the nature of the executed activity. This automation reduces user input requirements and streamlines workflows by eliminating the need for manual selection, particularly in scenarios where certain activities are frequently repeated. The invention enhances user experience by leveraging predictive algorithms to anticipate and perform actions on behalf of the user, improving efficiency and reducing cognitive load.
8. A method for streamlined data entry at a mobile device, comprising: receiving, from a server, data that identifies the one or more entities and a first interface that accepts selection among the identified one or more entities, wherein the one or more entities are identified based at least in part on most-recently-used (MRU) data for the mobile device; transmitting, to the server, selection of a particular entity responsive to transmitting the data and the first interface; receiving, from the server, a second interface that includes a list of activities that fits on a single screen of the mobile device and accepts selection among the list of activities, wherein the list of activities is determined based at least in part on the selection of the particular entity; transmitting, to the server, a selection of an activity of the list of activities; receiving, from the server, a comment entry user interface comprising automatically generated ghost text associated with the entity of the set of one or more entities and the selected activity; receiving, from a user of the mobile device and in the user interface, a user input value either accepting the ghost text or revising the ghost text; and transmitting, to the server, an indication of the user input value, either accepting the ghost text or revising the ghost text.
9. The method of claim 8 , further comprising: transmitting, to the server, context aware information for data logging associated with the entity of the set of one or more entities.
10. The method of claim 9 , wherein transmitting the context aware information for data logging comprises: determining a geographic location of the mobile device; and transmitting, to the server, the geographic location of the mobile device, wherein the set of one or more entities is based at least in part on the geographic location of the mobile device.
11. The method of claim 8 , further comprising: receiving, from the server, an indication of confirmation, wherein the indication of confirmation comprises confirmation of a selection of the entity of the set of the one or more entities, confirmation of a selection of an activity of the list of activities associated with the entity of the set of one or more entities, conformation of reception of the user input value either accepting the ghost text or revising the ghost text, confirmation of reception of implicit context-aware information, confirmation of successful logging of data at a data store, or a combination thereof; and displaying, in the user interface, the indication of confirmation.
12. A non-transitory computer-readable medium storing code for streamlined data entry at a server, the code comprising instructions executable by a processor to: query a cache for one or more most-recently-used (MRU) entities corresponding to a mobile device, wherein the cache stores a plurality of MRU entities based at least in part on a plurality of prior data logging events associated with the mobile device; automatically identify one or more entities corresponding to the mobile device as most likely to be selected for data logging according to the queried one or more MRU entities; transmit, for display at the mobile device, data that identifies the one or more entities and a first interface that accepts selection among the identified one or more entities; receive a selection of a particular entity responsive to transmitting the data and the first interface; transmit, for display at the mobile device, a second interface that includes a list of activities that fits on a single screen of the mobile device and accepts selection among the list of activities, wherein the list of activities is determined based at least in part on the selection of the particular entity; detect a selection of an activity of the list of activities responsive to transmitting the second interface; transmit, for display at the mobile device, a comment entry user interface comprising automatically generated ghost text, wherein the ghost text is automatically generated based at least in part on the selection of the particular entity and the selection of the activity; receive, from the mobile device, an indication of a user input value from the comment entry user interface either accepting the ghost text or revising the ghost text; and store, at a data store, an indication of at least the particular entity and the accepted or revised ghost text.
13. The non-transitory computer-readable medium of claim 12 , wherein the instructions are further executable to: receive, from the mobile device, context-aware information comprising a location of the mobile device, a user token, a time of data logging, or a combination thereof; and update the data store to include the context-aware information.
14. The non-transitory computer-readable medium of claim 12 , wherein the identification of the one or more entities as most likely to be selected for data logging is based at least in part on access recency of records of the one or more entities, imminence of events linked to the one or more entities, geographic proximity of the one or more entities to the mobile device, or a combination thereof.
15. The non-transitory computer-readable medium of claim 12 , wherein the instructions to detect the selection of the activity are further executable to: receive, from the mobile device, an indication of the activity selection among the list of activities, wherein the automatically generated ghost text is based at least in part on the activity selection; and execute an activity corresponding to the activity selection against the selected entity, wherein the storing is based at least in part on the executed activity.
Unknown
March 16, 2021
Browse 5M+ US patents with plain-English claim translations and AI-generated analysis.